Business Impact

  • Reduced the time taken to process system malfunctions with continuous monitoring, logging and alert generation

  • Modernized system by upgrading the existing infrastructure

  • Improved scalability and agility of the application by converting the monolithic application to microservices

Customer Key Facts

  • Location : United States
  • Industry : IT Services and IT Consulting

Problem Context 

The client is a leader in restaurant technology and has a tabletop, pay at the table, and e-commerce system installed in over 1800 restaurants in the US, allowing guests to have greater control over their dining experience.
They want to modernize the 33 APIs which run on Django, written over ten years ago


  • Changes were made with less business logic available
  • Limited documentation from the client’s side on the business logic of each APIs

Technologies Used

Amazon RDS
Amazon ElastiCache
Amazon Secrets Manager
Amazon WAF
Elastic Load Balancer

Solution Approach and Overview

  • Quantiphi modernized the entire backend of the client’s system, enabling the end-users to have greater control over their dining experience.
  • Upgraded the infrastructure in accordance with the best policies and scaled individual microservices

Solution Key Features

  • Converted monolithic applications to microservices by moving testing codes to Python’s latest versions – Django (1.7 to 4) and Python (2.7 to 3.9)
  • Upgraded dependencies for deprecated libraries and implemented Message Queue for communication between two microservices, scalability, and fault tolerance
  • Set up CI/CD pipelines for continuous integration and development
  • Built a BI & Data warehouse mechanism pointing to new databases
  • Performed unit tests in the dev environment to ensure a smooth data flow. 
  • Code deployment and testing in staging and production environments


Modernized the client’s backend system entirely and converted monolithic applications to microservices to deliver a more scalable and agile application

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